9,099 research outputs found

    Classification of Several Skin Cancer Types Based on Autofluorescence Intensity of Visible Light to Near Infrared Ratio

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    Skin cancer is a Malignant growth on the skin caused by many factors. The most common skin cancers are Basal Cell Cancer (BCC) and Squamous Cell Cancer (SCC). This research uses a discriminant analysis to classify some tissues of skin cancer based on criterion number of independent variables. An independent variable is variation of excitation light sources (LED lamp), filters, and sensors to measure autofluorescence intensity (IAF) of visible light to near infrared (VIS/NIR) ratio of paraffin embedded tissue biopsy from BCC, SCC, and Lipoma. From the result of discriminant analysis, it is known that the discriminant function is determined by 4 (four) independent variables i.e., blue LED-red filter, blue LED-yellow filter, UV LED-blue filter, and UV LED-yellow filter. The accuracy of discriminant in classifying the analysis of three skin cancer tissues is 100%

    Oblique Polarized Reflectance Spectroscopy for Depth Sensitive Measurements in the Epithelial Tissue

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    Optical spectroscopy has shown potential as a tool for precancer detection by discriminating alterations in the optical properties within epithelial tissues. Identifying depth-dependent alterations associated with the progression of epithelial cancerous lesions can be especially challenging in the oral cavity due to the variable thickness of the epithelium and the presence of keratinization. Optical spectroscopy of epithelial tissue with improved depth resolution would greatly assist in the isolation of optical properties associated with cancer progression. Here, we report a fiber optic probe for oblique polarized reflectance spectroscopy (OPRS) that is capable of depth sensitive detection by combining the following three approaches: multiple beveled fibers, oblique collection geometry, and polarization gating. We analyze how probe design parameters are related to improvements in collection efficiency of scattered photons from superficial tissue layers and to increased depth discrimination within epithelium. We have demonstrated that obliquely-oriented collection fibers increase both depth selectivity and collection efficiency of scattering signal. Currently, we evaluate this technology in a clinical trial of patients presenting lesions suspicious for dysplasia or carcinoma in the oral cavity. We use depth sensitive spectroscopic data to develop automated algorithms for analysis of morphological and architectural changes in the context of the multilayer oral epithelial tissue. Our initial results show that OPRS has the potential to improve the detection and monitoring of epithelial precancers in the oral cavity.Biomedical Engineerin

    Skin cancer detection by oblique-incidence diffuse reflectance spectroscopy

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    Skin cancer is the most common form of cancer and it is on the rise. If skin cancer is diagnosed early enough, the survival rate is close to 90%. Oblique-incidence diffuse reflectance (OIR) spectroscopy offers a technology that may be used in the clinic to aid physicians in diagnosing both melanoma and non-melanoma skin cancers. The system includes a halogen light source, a fiber optic probe, an imaging spectrograph, a charge coupled device (CCD) camera, and a computer. Light is delivered to the skin surface via optical fibers in the probe. After interacting with the skin, the light is collected and sent to the spectrograph that generates optical spectra. Images and histopathological diagnoses were obtained from 250 lesions at the University of Texas M.D. Anderson Cancer Center (Melanoma and Skin Center). To classify OIR data, an image processing algorithm was developed and evaluated for both pigmented and non-pigmented lesions. The continuous wavelet transform and the genetic algorithm were employed to extract optimal classification features. Bayes decision rule was used to categorize spatiospectral images based on the selected classification features. The overall classification accuracy for pigmented melanomas and severely dysplastic nevi is 100%. The overall classification accuracy for non-pigmented skin cancers and severely dysplastic nevi is 93.33%. Oblique-incidence diffuse reflectance spectroscopy and the developed algorithms have high classification rates and may prove useful in the clinic as the process is fast, noninvasive and accurate

    Recent Advances and the Potential for Clinical Use of Autofluorescence Detection of Extra-Ophthalmic Tissues

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    The autofluorescence (AF) characteristics of endogenous fluorophores allow the label-free assessment and visualization of cells and tissues of the human body. While AF imaging (AFI) is well-established in ophthalmology, its clinical applications are steadily expanding to other disciplines. This review summarizes clinical advances of AF techniques published during the past decade. A systematic search of the MEDLINE database and Cochrane Library databases was performed to identify clinical AF studies in extra-ophthalmic tissues. In total, 1097 articles were identified, of which 113 from internal medicine, surgery, oral medicine, and dermatology were reviewed. While comparable technological standards exist in diabetology and cardiology, in all other disciplines, comparability between studies is limited due to the number of differing AF techniques and non-standardized imaging and data analysis. Clear evidence was found for skin AF as a surrogate for blood glucose homeostasis or cardiovascular risk grading. In thyroid surgery, foremost, less experienced surgeons may benefit from the AF-guided intraoperative separation of parathyroid from thyroid tissue. There is a growing interest in AF techniques in clinical disciplines, and promising advances have been made during the past decade. However, further research and development are mandatory to overcome the existing limitations and to maximize the clinical benefits

    In Vivo Diagnosis of Melanoma and Nonmelanoma Skin Cancer Using Oblique Incidence Diffuse Reflectance Spectrometry

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    Early detection and treatment of skin cancer can significantly improve patient outcome. However, present standards for diagnosis require biopsy and histopathologic examinations that are relatively invasive, expensive, and difficult for patients with many early-stage lesions. Here, we show an oblique incidence diffuse reflectance spectroscopic (OIDRS) system that can be used for rapid skin cancer detection in vivo. This system was tested under clinical conditions by obtaining spectra from pigmented and nonpigmented skin lesions, including melanomas, differently staged dysplastic nevi, and common nevi that were validated by standard pathohistologic criteria. For diagnosis of pigmented melanoma, the data obtained achieved 90% sensitivity and specificity for a blinded test set. In a second analysis, we showed that this spectroscopy system can also differentiate nonpigmented basal cell or squamous cell carcinomas from noncancerous skin abnormalities, such as actinic keratoses and seborrheic keratoses, achieving 92% sensitivity and specificity. Taken together, our findings establish how OIDRS can be used to more rapidly and easily diagnose skin cancer in an accurate and automated manner in the clinic

    Epithelial cancer detection by oblique-incidence optical spectroscopy

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    This paper presents a study on non-invasive detection of two common epithelial cancers (skin and esophagus) based on oblique incidence diffuse reflectance spectroscopy (OIDRS). An OIDRS measurement system, which combines fiber optics and MEMS technologies, was developed. In our pilot studies, a total number of 137 cases have been measured in-vivo for skin cancer detection and a total number of 20 biopsy samples have been measured ex-vivo for esophageal cancer detection. To automatically differentiate the cancerous cases from benign ones, a statistical software classification program was also developed. An overall classification accuracy of 90% and 100% has been achieved for skin and esophageal cancer classification, respectively

    White-light oblique-incidence diffuse reflectance spectroscopy for classification of in-vivo pigmented skin lesions

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    A study of in-vivo classification of pigmented skin lesions using oblique-incidence diffuse reflectance spectroscopy is presented. Spatio-spectral data in the wavelength range from 455 to 765 nm are collected from 111 pigmented lesions including 10 histopathologically diagnosed as melanoma. The first 67 lesions are used for training the classifiers, and 44 lesions are used for testing. The first classifier separates (1) malignant melanoma and severe dysplastic nevi from (2) moderate and mild dysplastic nevi, common nevi, actinic and seborrheic keratoses. The second classifier next distinguishes between (a) moderate and mild dysplastic nevi, common nevi from (b) actinic and seborrheic keratoses. The third classifier further separates (I) moderate and mild dysplastic nevi from (II) common nevi. The first classifier performs with 100% sensitivity and 91% specificity with overall classification rates of 93% and 95 % for the training and testing sets, respectively. The second classifier has classification rates of 95% and 97 % for the training and testing sets, respectively, whereas the third classifier has classification rates of 98% and 94 % for the training and testing sets, respectively

    Comparative analysis of diagnostic techniques for melanoma detection: a systematic review of diagnostic test accuracy studies and meta-analysis

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    Melanoma has the highest mortality rate among skin cancers, and early-diagnosis is essential to maximize survival rate. The current procedure for melanoma diagnosis is based on dermoscopy, i.e., a qualitative visual inspection of lesions with intrinsic limited diagnostic reliability and reproducibility. Other non-invasive diagnostic techniques may represent valuable solutions to retrieve additional objective information of a lesion. This review aims to compare the diagnostic performance of non-invasive techniques, alternative to dermoscopy, for melanoma detection in clinical settings. A systematic review of the available literature was performed using PubMed, Scopus and Google scholar databases (2010-September 2020). All human, in-vivo, non-invasive studies using techniques, alternative to dermoscopy, for melanoma diagnosis were included with no restriction on the recruited population. The reference standard was histology but dermoscopy was accepted only in case of benign lesions. Attributes of the analyzed studies were compared, and the quality was evaluated using CASP Checklist. For studies in which the investigated technique was implemented as a diagnostic tool (DTA studies), the QUADAS-2 tool was applied. For DTA studies that implemented a melanoma vs. other skin lesions classification task, a meta-analysis was performed reporting the SROC curves. Sixty-two references were included in the review, of which thirty-eight were analyzed using QUADAS-2. Study designs were: clinical trials (13), retrospective studies (10), prospective studies (8), pilot studies (10), multitiered study (1); the remain studies were proof of concept or had undefined study type. Studies were divided in categories based on the physical principle employed by each diagnostic technique. Twenty-nine out of thirty-eight DTA studies were included in the meta-analysis. Heterogeneity of studies' types, testing strategy, and diagnostic task limited the systematic comparison of the techniques. Based on the SROC curves, spectroscopy achieved the best performance in terms of sensitivity (93%, 95% CI 92.8-93.2%) and specificity (85.2%, 95%CI 84.9-85.5%), even though there was high concern regarding robustness of metrics. Reflectance-confocal-microscopy, instead, demonstrated higher robustness and a good diagnostic performance (sensitivity 88.2%, 80.3-93.1%; specificity 65.2%, 55-74.2%). Best practice recommendations were proposed to reduce bias in future DTA studies. Particular attention should be dedicated to widen the use of alternative techniques to conventional dermoscopy

    Oblique-incidence spatially resolved diffuse reflectance spectroscopic diagnosis of skin cancer

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    This paper presents the use of spatially resolved oblique-incidence diffuse reflectance spectroscopy for skin cancer diagnosis. Spatio-spectral data from 166 pigmented skin lesions were collected for the wavelength range from 455 to 765 nm. A set of neural network based classifiers separates the pigmented malignant melanomas from the benign and dysplastic subgroups. A total of 110 lesions were used as the training set and 56 lesions were used as the testing set. This classifier performs with an overall 100% sensitivity and 92% specificity for the training set and 100% sensitivity and 88% specificity for the testing set. The second classifier was designed to separate the benign from the dysplastic subgroups. For the second classifier a total of 100 lesions were used as the training set and 51 lesions were used as the testing set. The overall classification rates were 94% and 88% for the training and testing sets respectively
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